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http://bura.brunel.ac.uk/handle/2438/25653Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Abakah, EJA | - |
| dc.contributor.author | Caporale, GM | - |
| dc.contributor.author | Gil-Alana, LA | - |
| dc.date.accessioned | 2022-12-19T08:29:17Z | - |
| dc.date.available | 2022-12-19T08:29:17Z | - |
| dc.date.issued | 2022-12-20 | - |
| dc.identifier | ORCID iD: Guglielmo Maria Caporale https://orcid.org/0000-0002-0144-4135 | - |
| dc.identifier | 2159736 | - |
| dc.identifier.citation | Abakah, E.J.A., Caporale, G.M. and Gil-Alana, L.A. (2023) 'The effects of us covid-19 policy responses on cryptocurrencies, fintech and artificial intelligence stocks: A fractional integration analysis', Cogent Economics and Finance, 10 (1), 2159736, pp. 1 - 14. doi: 10.1080/23322039.2022.2159736. | en_US |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/25653 | - |
| dc.description.abstract | Copyright © 2022 The Author(s). This paper assesses the impact of US policy responses to the Covid-19 pandemic on various technology-related assets such as cryptocurrencies, financial technology, and artificial intelligence stocks using fractional integration techniques. More precisely, it analyzes the behavior of the percentage returns in the case of nine major coins (Bitcoin—BITC, Stella—STEL, Litecoin—LITE, Ethereum—ETHE, XRP (Ripple), Dash, Monero—MONE, NEM, Tether—TETH) and two technology-related stock market indices (the KBW NASDAQ Technology Index—KFTX, and the NASDAQ Artificial Intelligence index—AI) over the period 1 January 2020–5 March 2021. The results suggest that fiscal measures such as debt relief and fiscal policy announcements had positive effects on the series examined during the pandemic, when an increased mortality rate tended instead to drive them down; by contrast, monetary measures and announcements appear to have had very little impact and the Covid-19 containment measures none at all. | - |
| dc.description.sponsorship | The authors received no direct funding for this research. Luis A. Gil-Alana gratefully acknowledges the financial support from the Grant PID2020-113691RB-I00 funded by MCIN/AEI/ 10.13039/501100011033. | - |
| dc.format.extent | 1 - 14 | - |
| dc.format.medium | Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Cogent OA (Taylor & Francis) | en_US |
| dc.rights | Copyright © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. You are free to: Share — copy and redistribute the material in any medium or format. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. | - |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
| dc.subject | Covid-19 pandemic | en_US |
| dc.subject | cryptocurrencies | en_US |
| dc.subject | Fintech | en_US |
| dc.subject | artificial intelligence | en_US |
| dc.subject | Covid-19 policies | en_US |
| dc.subject | fractional integration | en_US |
| dc.title | The effects of us covid-19 policy responses on cryptocurrencies, fintech and artificial intelligence stocks: A fractional integration analysis | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1080/23322039.2022.2159736 | - |
| dc.relation.isPartOf | Cogent Economics and Finance | - |
| pubs.issue | 1 | - |
| pubs.publication-status | Published online | - |
| pubs.volume | 10 | - |
| dc.identifier.eissn | 2332-2039 | - |
| dc.rights.holder | The Author(s) | - |
| Appears in Collections: | Dept of Economics and Finance Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. You are free to: Share — copy and redistribute the material in any medium or format. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. | 1.58 MB | Adobe PDF | View/Open |
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